Dataset Information

Camouflage, detection and identification of moving targets.

ABSTRACT: Nearly all research on camouflage has investigated its effectiveness for concealing stationary objects. However, animals have to move, and patterns that only work when the subject is static will heavily constrain behaviour. We investigated the effects of different camouflages on the three stages of predation-detection, identification and capture-in a computer-based task with humans. An initial experiment tested seven camouflage strategies on static stimuli. In line with previous literature, background-matching and disruptive patterns were found to be most successful. Experiment 2 showed that if stimuli move, an isolated moving object on a stationary background cannot avoid detection or capture regardless of the type of camouflage. Experiment 3 used an identification task and showed that while camouflage is unable to slow detection or capture, camouflaged targets are harder to identify than uncamouflaged targets when similar background objects are present. The specific details of the camouflage patterns have little impact on this effect. If one has to move, camouflage cannot impede detection; but if one is surrounded by similar targets (e.g. other animals in a herd, or moving background distractors), then camouflage can slow identification. Despite previous assumptions, motion does not entirely 'break' camouflage.

SUBMITTER: Hall JR

PROVIDER: S-EPMC3619462 | biostudies-literature | 2013 May

REPOSITORIES: biostudies-literature

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Camouflage, detection and identification of moving targets.

Hall Joanna R JR Cuthill Innes C IC Baddeley Roland R Shohet Adam J AJ Scott-Samuel Nicholas E NE

Proceedings. Biological sciences 20130313 1758

Nearly all research on camouflage has investigated its effectiveness for concealing stationary objects. However, animals have to move, and patterns that only work when the subject is static will heavily constrain behaviour. We investigated the effects of different camouflages on the three stages of predation-detection, identification and capture-in a computer-based task with humans. An initial experiment tested seven camouflage strategies on static stimuli. In line with previous literature, back ...[more]

PMID: 23486439

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Project description:PurposeWhile four-dimensional computed tomography (4DCT) and deformable registration can be used to assess the dose delivered to regularly moving targets, there are few methods available for irregularly moving targets. 4DCT captures an idealized waveform, but human respiration during treatment is characterized by gradual baseline shifts and other deviations from a periodic signal. This paper describes a method for computing the dose delivered to irregularly moving targets based on 1D or 3D waveforms captured at the time of delivery.MethodsThe procedure uses CT or 4DCT images for dose calculation, and 1D or 3D respiratory waveforms of the target position at time of delivery. Dose volumes are converted from their Cartesian geometry into a beam-specific radiological depth space, parameterized in 2D by the beam aperture, and longitudinally by the radiological depth. In this new frame of reference, the proton doses are translated according to the motion found in the 1D or 3D trajectory. These translated dose volumes are weighted and summed, then transformed back into Cartesian space, yielding an estimate of the dose that includes the effect of the measured breathing motion. The method was validated using a synthetic lung phantom and a single representative patient CT. Simulated 4DCT was generated for the phantom with 2 cm peak-to-peak motion.ResultsA passively-scattered proton treatment plan was generated using 6 mm and 5 mm smearing for the phantom and patient plans, respectively. The method was tested without motion, and with two simulated breathing signals: a 2 cm amplitude sinusoid, and a 2 cm amplitude sinusoid with 3 cm linear drift in the phantom. The tumor positions were equally weighted for the patient calculation. Motion-corrected dose was computed based on the mid-ventilation CT image in the phantom and the peak exhale position in the patient. Gamma evaluation was 97.8% without motion, 95.7% for 2 cm sinusoidal motion, 95.7% with 3 cm drift in the phantom (2 mm, 2%), and 90.8% (3 mm, 3%)for the patient data.ConclusionsWe have demonstrated a method for accurately reproducing proton dose to an irregularly moving target from a single CT image. We believe this algorithm could prove a useful tool to study the dosimetric impact of baseline shifts either before or during treatment.

Dataset Information

Camouflage, detection and identification of moving targets.

Publications

Camouflage, detection and identification of moving targets.

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